Manufacturing facilities employ various types of transfer lines and networks with workstations and buffers. This approach promotes the production and fabrication of multicomponent equipments and systems. Analysis of these lines requires the application of discrete time Markov Chain methods. These methods when computerized present certain problems concerning the data storage of large sparse transition matrices. Repetitive multiplication techniques were used to provide the general Markov Chain solution for a series transfer line. These solutions were then computerized to evaluate the series line's availability trajectory. The limiting (leveling off) point for each trajectory provided the steady state availability. From these solutions the work then focuses on the development of new computer algorithms for the series transfer line configuration. These algorithms employ advanced techniques to minimize the storage of large sparse vectors and matices while maintaining relatively fast computational times. The algorithms rely on the line's transition matrix decomposition via graph theoretic methods. A set of library functions written in the C language were specially written to manipulate the Markov Chain matrix and vector data. An extensive set of results were analyzed for the three and four workstation series transfer lines. This analysis employed linear model regression techniques. Results were also collected for the five workstation line. These results show a marked improvement in overall availability when the line's last workstation has a high reliability. In addition, preliminary results indicate that three and four workstation series lines' overall availability are linear combinations of each workstation's availability. Finally, proposed topics for future research are presented in eight major areas. These topics include the development of models for parallel series, series parallel, feedback control, assembly, and disassembly type lines. Also, approximation models and decomposition methods are described in detail.

Manufacturing facilities employ various types of transfer lines and networks with workstations and buffers. This approach promotes the production and fabrication of multicomponent equipments and systems. Analysis of these lines requires the application of discrete time Markov Chain methods. These methods when computerized present certain problems concerning the data storage of large sparse transition matrices. Repetitive multiplication techniques were used to provide the general Markov Chain solution for a series transfer line. These solutions were then computerized to evaluate the series line's availability trajectory. The limiting (leveling off) point for each trajectory provided the steady state availability. From these solutions the work then focuses on the development of new computer algorithms for the series transfer line configuration. These algorithms employ advanced techniques to minimize the storage of large sparse vectors and matices while maintaining relatively fast computational times. The algorithms rely on the line's transition matrix decomposition via graph theoretic methods. A set of library functions written in the C language were specially written to manipulate the Markov Chain matrix and vector data. An extensive set of results were analyzed for the three and four workstation series transfer lines. This analysis employed linear model regression techniques. Results were also collected for the five workstation line. These results show a marked improvement in overall availability when the line's last workstation has a high reliability. In addition, preliminary results indicate that three and four workstation series lines' overall availability are linear combinations of each workstation's availability. Finally, proposed topics for future research are presented in eight major areas. These topics include the development of models for parallel series, series parallel, feedback control, assembly, and disassembly type lines. Also, approximation models and decomposition methods are described in detail.

en_US

dc.type

text

en_US

dc.type

Dissertation-Reproduction (electronic)

en_US

dc.subject

Engineering.

en_US

thesis.degree.name

Ph.D.

en_US

thesis.degree.level

doctoral

en_US

thesis.degree.discipline

Systems and Industrial Engineering

en_US

thesis.degree.discipline

Graduate College

en_US

thesis.degree.grantor

University of Arizona

en_US

dc.contributor.advisor

Dietrich, Duane L.

en_US

dc.contributor.committeemember

Askin, Ronald G.

en_US

dc.contributor.committeemember

Szidarovszky, Ferenc

en_US

dc.contributor.committeemember

Weber, Jean E.

en_US

dc.contributor.committeemember

Denny, John L.

en_US

dc.identifier.proquest

9114059

en_US

dc.identifier.oclc

710844362

en_US

All Items in UA Campus Repository are protected by copyright, with all rights reserved, unless otherwise indicated.